8 papers · 1 filter
Relightable Gaussian Splatting for Virtual Production Using Image-Based Illumination
Adrian Azzarelli, Nantheera Anantrasirichai, James Pollock +1
Virtual production (VP) use LED walls to provide both background imagery and image-based lighting. While this enables on-set compositing, it couples lighting to background and scen…
Splatography: Sparse multi-view dynamic Gaussian Splatting for filmmaking challenges
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. How…
ViVo: A Dataset for Volumetric Video Reconstruction and Compression
Adrian Azzarelli, Ge Gao, Ho Man Kwan +4
As research on neural volumetric video reconstruction and compression flourishes, there is a need for diverse and realistic datasets, which can be used to develop and validate reco…
AquaNeRF: Neural Radiance Fields in Underwater Media with Distractor Removal
Luca Gough, Adrian Azzarelli, Fan Zhang +1
Neural radiance field (NeRF) research has made significant progress in modeling static video content captured in the wild. However, current models and rendering processes rarely co…
Exploring Dynamic Novel View Synthesis Technologies for Cinematography
Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull
Novel view synthesis (NVS) has shown significant promise for applications in cinematographic production, particularly through the exploitation of Neural Radiance Fields (NeRF) and…
BVI-CR: A Multi-View Human Dataset for Volumetric Video Compression
Ge Gao, Adrian Azzarelli, Ho Man Kwan +4
The advances in immersive technologies and 3D reconstruction have enabled the creation of digital replicas of real-world objects and environments with fine details. These processes…